Toward a Standard Approach for Echo Chamber Detection: Reddit Case Study
Source abstract
Abstract
In a digital environment, the term echo chamber refers to an alarming phenomenon in which beliefs are amplified or reinforced by communication repetition inside a closed system and insulated from rebuttal. Up to date, a formal definition, as well as a platform-independent approach for its detection, is still lacking. This paper proposes a general framework to identify echo chambers on online social networks built on top of features they commonly share. Our approach is based on a four-step pipeline that involves (i) the identification of a controversial issue; (ii) the inference of users’ ideology on the controversy; (iii) the construction of users’ debate network; and (iv) the detection of homogeneous meso-scale communities. We further apply our framework in a detailed case study on Reddit, covering the first two and a half years of Donald Trump’s presidency. Our main purpose is to assess the existence of Pro-Trump and Anti-Trump echo chambers among three sociopolitical issues, as well as to analyze their stability and consistency over time. Even if users appear strongly polarized with respect to their ideology, most tend not to insulate themselves in echo chambers. However, the found polarized communities were proven to be definitely stable over time.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Opinion Dynamics and Social Influence · Misinformation and Its Impacts · Social Media and Politics
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
KDD Lab, CNR-ISTI, 56126 Pisa, Italy
KDD Lab, University of Pisa, 56126 Pisa, Italy
Funding
INFRAIA-01-2018-2019: Research and Innovation action
References (60)
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